If you want the code to run natively, or if you require a little more customization and flexibility, go for TensorFlow Lite.

Google's TensorFlow Lite model maker tool adapts state-of-the-art machine learning models for on-device applications, chiefly NLP and computer vision.

The basic idea of TensorFlow Lite is that you train a full-blown TensorFlow model and convert it to the TensorFlow Lite model format. Then you can use the converted file in your mobile application ...

There are three major components of the TensorFlow Lite architectural design, namely the TensorFlow Model, the TensorFlow Lite converter, and the TensorFlow Lite Model file.

TensorFlow is a Python-friendly open source library for developing machine learning applications and neural networks. Here's what you need to know about TensorFlow.

TensorFlow Lite (TFLite) was announced in 2017 and Google is now calling it “LiteRT” to reflect how it supports third-party models. TensorFlow Lite for mobile on-device AI has “grown beyond ...

A new multifunctional Edge AI camera offering nightvision, motion detection, TensorFlow Lite support, no-code set up and open source design ...

For them there’s TensorFlow Lite, in which a model is created on a larger machine and exported to a microcontroller or similarly resource-constrained one.

Google LLC today announced a new tool called TensorFlow Lite Model Maker, which uses a technique known as transfer learning to adapt machine learning models to custom data sets. TensorFlow Lite is ...

Google today released a tool that converts AI models produced for mobile devices using its TensorFlow Lite tool into Apple’s Core ML .mlmodel file format for use with iOS devices.